Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	553649
Missing cells	255332
Missing cells (%)	2.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	84.5 MiB
Average record size in memory	160.0 B

Variable types

Numeric	8
Categorical	10
Boolean	2

Alerts

`FLAG_MOBIL` has constant value "1"	Constant
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN`	High correlation
`OCCUPATION_TYPE` is highly correlated with `FLAG_MOBIL` and 1 other fields	High correlation
`NAME_INCOME_TYPE` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_PHONE` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_OWN_REALTY` is highly correlated with `FLAG_MOBIL`	High correlation
`NAME_FAMILY_STATUS` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_OWN_CAR` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_WORK_PHONE` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_EMAIL` is highly correlated with `FLAG_MOBIL`	High correlation
`NAME_EDUCATION_TYPE` is highly correlated with `FLAG_MOBIL`	High correlation
`FLAG_MOBIL` is highly correlated with `OCCUPATION_TYPE` and 10 other fields	High correlation
`NAME_HOUSING_TYPE` is highly correlated with `FLAG_MOBIL`	High correlation
`CODE_GENDER` is highly correlated with `OCCUPATION_TYPE` and 1 other fields	High correlation
`CODE_GENDER` is highly correlated with `FLAG_OWN_CAR` and 1 other fields	High correlation
`FLAG_OWN_CAR` is highly correlated with `CODE_GENDER`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`NAME_INCOME_TYPE` is highly correlated with `AGE`	High correlation
`OCCUPATION_TYPE` is highly correlated with `CODE_GENDER`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN`	High correlation
`AGE` is highly correlated with `NAME_INCOME_TYPE`	High correlation
`OCCUPATION_TYPE` has 170608 (30.8%) missing values	Missing
`MONTHS_BALANCE` has 84724 (15.3%) missing values	Missing
`CNT_CHILDREN` has 387335 (70.0%) zeros	Zeros
`YEARS_EMPLOYED` has 94948 (17.1%) zeros	Zeros
`MONTHS_BALANCE` has 13392 (2.4%) zeros	Zeros
`STATUS` has 187137 (33.8%) zeros	Zeros

Reproduction

Analysis started	2022-04-14 19:01:29.395717
Analysis finished	2022-04-14 19:03:06.279606
Duration	1 minute and 36.88 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

ID
Real number (ℝ_≥0)

Distinct	116469
Distinct (%)	21.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5221598.844

Minimum	5008804
Maximum	7995770
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	5008804
5-th percentile	5021656
Q1	5047637
median	5091335
Q3	5135972
95-th percentile	6230229
Maximum	7995770
Range	2986966
Interquartile range (IQR)	88335

Descriptive statistics

Standard deviation	385684.2599
Coefficient of variation (CV)	0.07386324983
Kurtosis	6.163223595
Mean	5221598.844
Median Absolute Deviation (MAD)	44637
Skewness	2.659772059
Sum	2.890932978 × 10¹²
Variance	1.487523483 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5115960	61	< 0.1%
5089650	61	< 0.1%
5089683	61	< 0.1%
5037153	61	< 0.1%
5118192	61	< 0.1%
5095470	61	< 0.1%
5010943	61	< 0.1%
5029158	61	< 0.1%
5105682	61	< 0.1%
5117576	61	< 0.1%
Other values (116459)	553039	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5008804	16	< 0.1%
5008805	3	< 0.1%
5008806	30	< 0.1%
5008808	5	< 0.1%
5008809	5	< 0.1%
5008810	24	< 0.1%
5008811	24	< 0.1%
5008812	17	< 0.1%
5008813	7	< 0.1%
5008814	3	< 0.1%

Value	Count	Frequency (%)
7995770	1	< 0.1%
7965248	1	< 0.1%
7836902	1	< 0.1%
7823595	1	< 0.1%
7744440	1	< 0.1%
7728066	1	< 0.1%
7702833	1	< 0.1%
7702238	1	< 0.1%
7618936	1	< 0.1%
7583486	1	< 0.1%

CODE_GENDER
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

F	364348
M	189301

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	M
2nd row	M
3rd row	M
4th row	M
5th row	M

Common Values

Value	Count	Frequency (%)
F	364348	65.8%
M	189301	34.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	364348	65.8%
m	189301	34.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_OWN_CAR
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	540.8 KiB

False	342813
True	210836

Common Values
Chart

Value	Count	Frequency (%)
False	342813	61.9%
True	210836	38.1%

FLAG_OWN_REALTY
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	540.8 KiB

True	368911
False	184738

Common Values
Chart

Value	Count	Frequency (%)
True	368911	66.6%
False	184738	33.4%

CNT_CHILDREN
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4218286315

Minimum	0
Maximum	19
Zeros	387335
Zeros (%)	70.0%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	19
Range	19
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.7439695718
Coefficient of variation (CV)	1.763677276
Kurtosis	22.57659933
Mean	0.4218286315
Median Absolute Deviation (MAD)	0
Skewness	2.674298427
Sum	233545
Variance	0.5534907238
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
0	387335	70.0%
1	109521	19.8%
2	48849	8.8%
3	6695	1.2%
4	881	0.2%
5	241	< 0.1%
14	78	< 0.1%
7	39	< 0.1%
19	6	< 0.1%
6	2	< 0.1%
Other values (2)	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	387335	70.0%
1	109521	19.8%
2	48849	8.8%
3	6695	1.2%
4	881	0.2%
5	241	< 0.1%
6	2	< 0.1%
7	39	< 0.1%
9	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
19	6	< 0.1%
14	78	< 0.1%
12	1	< 0.1%
9	1	< 0.1%
7	39	< 0.1%
6	2	< 0.1%
5	241	< 0.1%
4	881	0.2%
3	6695	1.2%
2	48849	8.8%

AMT_INCOME_TOTAL
Real number (ℝ_≥0)

Distinct	866
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	184791.9778

Minimum	26100
Maximum	6750000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	26100
5-th percentile	72000
Q1	117000
median	157500
Q3	225000
95-th percentile	360000
Maximum	6750000
Range	6723900
Interquartile range (IQR)	108000

Descriptive statistics

Standard deviation	101336.2185
Coefficient of variation (CV)	0.548379966
Kurtosis	64.22692669
Mean	184791.9778
Median Absolute Deviation (MAD)	45000
Skewness	3.547587469
Sum	1.023098937 × 10¹¹
Variance	1.026902918 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
135000	64256	11.6%
180000	47971	8.7%
157500	47278	8.5%
112500	46028	8.3%
225000	42995	7.8%
202500	34166	6.2%
90000	27434	5.0%
270000	25353	4.6%
315000	14738	2.7%
67500	13920	2.5%
Other values (856)	189510	34.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
26100	1	< 0.1%
27000	82	< 0.1%
27900	2	< 0.1%
28350	1	< 0.1%
28723.5	1	< 0.1%
28800	1	< 0.1%
29133	1	< 0.1%
29250	47	< 0.1%
30150	65	< 0.1%
30600	1	< 0.1%

Value	Count	Frequency (%)
6750000	1	< 0.1%
4500000	1	< 0.1%
3950059.5	1	< 0.1%
3825000	1	< 0.1%
3375000	1	< 0.1%
3150000	1	< 0.1%
2214117	1	< 0.1%
2025000	3	< 0.1%
1890000	2	< 0.1%
1800000	2	< 0.1%

NAME_INCOME_TYPE
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

Working	282413
Commercial associate	130394
Pensioner	95504
State servant	45190
Student	148

Length

Max length	20
Median length	7
Mean length	10.89645786
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Working
2nd row	Working
3rd row	Working
4th row	Working
5th row	Working

Common Values

Value	Count	Frequency (%)
Working	282413	51.0%
Commercial associate	130394	23.6%
Pensioner	95504	17.2%
State servant	45190	8.2%
Student	148	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
working	282413	38.7%
commercial	130394	17.9%
associate	130394	17.9%
pensioner	95504	13.1%
state	45190	6.2%
servant	45190	6.2%
student	148	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_EDUCATION_TYPE
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

Secondary / secondary special	379642
Higher education	146949
Incomplete higher	20450
Lower secondary	6196
Academic degree	412

Length

Max length	29
Median length	29
Mean length	24.939216
Min length	15

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Higher education
2nd row	Higher education
3rd row	Higher education
4th row	Higher education
5th row	Higher education

Common Values

Value	Count	Frequency (%)
Secondary / secondary special	379642	68.6%
Higher education	146949	26.5%
Incomplete higher	20450	3.7%
Lower secondary	6196	1.1%
Academic degree	412	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
secondary	765480	41.0%
	379642	20.3%
special	379642	20.3%
higher	167399	9.0%
education	146949	7.9%
incomplete	20450	1.1%
lower	6196	0.3%
academic	412	< 0.1%
degree	412	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_FAMILY_STATUS
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

Married	382670
Single / not married	69919
Civil marriage	44677
Separated	32644
Widow	23739

Length

Max length	20
Median length	7
Mean length	9.238775831
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Civil marriage
2nd row	Civil marriage
3rd row	Civil marriage
4th row	Civil marriage
5th row	Civil marriage

Common Values

Value	Count	Frequency (%)
Married	382670	69.1%
Single / not married	69919	12.6%
Civil marriage	44677	8.1%
Separated	32644	5.9%
Widow	23739	4.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
married	452589	56.0%
single	69919	8.7%
	69919	8.7%
not	69919	8.7%
civil	44677	5.5%
marriage	44677	5.5%
separated	32644	4.0%
widow	23739	2.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_HOUSING_TYPE
Categorical

HIGH CORRELATION

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

House / apartment	496580
With parents	24683
Municipal apartment	18369
Rented apartment	7324
Office apartment	4367

Length

Max length	19
Median length	17
Mean length	16.81392543
Min length	12

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Rented apartment
2nd row	Rented apartment
3rd row	Rented apartment
4th row	Rented apartment
5th row	Rented apartment

Common Values

Value	Count	Frequency (%)
House / apartment	496580	89.7%
With parents	24683	4.5%
Municipal apartment	18369	3.3%
Rented apartment	7324	1.3%
Office apartment	4367	0.8%
Co-op apartment	2326	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
apartment	528966	33.0%
house	496580	31.0%
	496580	31.0%
with	24683	1.5%
parents	24683	1.5%
municipal	18369	1.1%
rented	7324	0.5%
office	4367	0.3%
co-op	2326	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_MOBIL
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

1	553649

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	553649	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	553649	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_WORK_PHONE
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

0	430843
1	122806

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	430843	77.8%
1	122806	22.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	430843	77.8%
1	122806	22.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_PHONE
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

0	390891
1	162758

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	390891	70.6%
1	162758	29.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	390891	70.6%
1	162758	29.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_EMAIL
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.2 MiB

0	503217
1	50432

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	503217	90.9%
1	50432	9.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	503217	90.9%
1	50432	9.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

OCCUPATION_TYPE
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	18
Distinct (%)	< 0.1%
Missing	170608
Missing (%)	30.8%
Memory size	4.2 MiB

Laborers	95859
Core staff	52290
Sales staff	51157
Managers	46593
Drivers	35649
Other values (13)	101493

Length

Max length	21
Median length	10
Mean length	10.49062894
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Security staff
2nd row	Security staff
3rd row	Security staff
4th row	Security staff
5th row	Security staff

Common Values

Value	Count	Frequency (%)
Laborers	95859	17.3%
Core staff	52290	9.4%
Sales staff	51157	9.2%
Managers	46593	8.4%
Drivers	35649	6.4%
High skill tech staff	21924	4.0%
Accountants	18404	3.3%
Medicine staff	18089	3.3%
Cooking staff	10093	1.8%
Security staff	9878	1.8%
Other values (8)	23105	4.2%
(Missing)	170608	30.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
staff	180477	29.3%
laborers	98625	16.0%
core	52290	8.5%
sales	51157	8.3%
managers	46593	7.6%
drivers	35649	5.8%
high	21924	3.6%
skill	21924	3.6%
tech	21924	3.6%
accountants	18404	3.0%
Other values (13)	66671	10.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

CNT_FAM_MEMBERS
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.194200658

Minimum	1
Maximum	20
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	3
95-th percentile	4
Maximum	20
Range	19
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9088151052
Coefficient of variation (CV)	0.4141896057
Kurtosis	8.223231439
Mean	2.194200658
Median Absolute Deviation (MAD)	0
Skewness	1.357786315
Sum	1214817
Variance	0.8259448954
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
2	300066	54.2%
1	104850	18.9%
3	95009	17.2%
4	46116	8.3%
5	6413	1.2%
6	879	0.2%
7	189	< 0.1%
15	78	< 0.1%
9	39	< 0.1%
20	6	< 0.1%
Other values (3)	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	104850	18.9%
2	300066	54.2%
3	95009	17.2%
4	46116	8.3%
5	6413	1.2%
6	879	0.2%
7	189	< 0.1%
8	2	< 0.1%
9	39	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
20	6	< 0.1%
15	78	< 0.1%
14	1	< 0.1%
11	1	< 0.1%
9	39	< 0.1%
8	2	< 0.1%
7	189	< 0.1%
6	879	0.2%
5	6413	1.2%
4	46116	8.3%

AGE
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	16379
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	44.13554696

Minimum	20.50418558
Maximum	68.99799448
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	20.50418558
5-th percentile	27.33252565
Q1	34.69201969
median	43.18500722
Q3	53.58084013
95-th percentile	63.00745395
Maximum	68.99799448
Range	48.49380891
Interquartile range (IQR)	18.88882044

Descriptive statistics

Standard deviation	11.36108862
Coefficient of variation (CV)	0.257413568
Kurtosis	-1.039538549
Mean	44.13554696
Median Absolute Deviation (MAD)	9.317097545
Skewness	0.1541479961
Sum	24435601.44
Variance	129.0743346
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
41.45191209	419	0.1%
40.15688207	416	0.1%
42.91669233	398	0.1%
38.70305345	378	0.1%
32.79465013	377	0.1%
27.86367961	354	0.1%
38.69483973	348	0.1%
40.86599999	346	0.1%
55.15513666	327	0.1%
46.25967679	324	0.1%
Other values (16369)	549962	99.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
20.50418558	1	< 0.1%
21.02165	1	< 0.1%
21.02712581	1	< 0.1%
21.04902907	1	< 0.1%
21.07914605	1	< 0.1%
21.09557349	5	< 0.1%
21.14485581	1	< 0.1%
21.14759372	1	< 0.1%
21.23794465	30	< 0.1%
21.25711	1	< 0.1%

Value	Count	Frequency (%)
68.99799448	1	< 0.1%
68.88300239	1	< 0.1%
68.86383704	51	< 0.1%
68.86109913	1	< 0.1%
68.83098216	56	< 0.1%
68.77896192	1	< 0.1%
68.72146588	1	< 0.1%
68.71872797	32	< 0.1%
68.70230053	1	< 0.1%
68.68861099	33	< 0.1%

YEARS_EMPLOYED
Real number (ℝ_≥0)

ZEROS

Distinct	9406
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.09114325

Minimum	0
Maximum	47.99824774
Zeros	94948
Zeros (%)	17.1%
Negative	0
Negative (%)	0.0%
Memory size	4.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1.054094198
median	4.26292121
Q3	8.761302422
95-th percentile	19.8881565
Maximum	47.99824774
Range	47.99824774
Interquartile range (IQR)	7.707208225

Descriptive statistics

Standard deviation	6.585870321
Coefficient of variation (CV)	1.081220725
Kurtosis	3.737188483
Mean	6.09114325
Median Absolute Deviation (MAD)	3.657843761
Skewness	1.741275298
Sum	3372355.369
Variance	43.37368789
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	94948	17.1%
1.09790071	922	0.2%
0.2956939568	828	0.1%
4.213638884	784	0.1%
4.794075169	779	0.1%
0.5475814014	751	0.1%
5.212974941	720	0.1%
6.929642635	677	0.1%
4.961087497	661	0.1%
0.8460132652	660	0.1%
Other values (9396)	451919	81.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	94948	17.1%
0.03285488408	2	< 0.1%
0.03559279109	2	< 0.1%
0.04380651211	5	< 0.1%
0.04654441912	21	< 0.1%
0.04928232613	1	< 0.1%
0.05202023313	1	< 0.1%
0.06023395415	2	< 0.1%
0.06297186116	1	< 0.1%
0.06570976817	2	< 0.1%

Value	Count	Frequency (%)
47.99824774	1	< 0.1%
45.90648679	1	< 0.1%
45.16177608	2	< 0.1%
44.80584817	1	< 0.1%
44.74561422	1	< 0.1%
44.40885165	1	< 0.1%
44.17612956	1	< 0.1%
44.08851653	1	< 0.1%
43.42320513	1	< 0.1%
43.0207328	18	< 0.1%

MONTHS_BALANCE
Real number (ℝ)

MISSING
ZEROS

Distinct	61
Distinct (%)	< 0.1%
Missing	84724
Missing (%)	15.3%
Infinite	0
Infinite (%)	0.0%
Mean	-20.97951272

Minimum	-60
Maximum	0
Zeros	13392
Zeros (%)	2.4%
Negative	455533
Negative (%)	82.3%
Memory size	4.2 MiB

Quantile statistics

Minimum	-60
5-th percentile	-48
Q1	-32
median	-19
Q3	-8
95-th percentile	-1
Maximum	0
Range	60
Interquartile range (IQR)	24

Descriptive statistics

Standard deviation	14.68052272
Coefficient of variation (CV)	-0.6997551812
Kurtosis	-0.7197345295
Mean	-20.97951272
Median Absolute Deviation (MAD)	11
Skewness	-0.4838080213
Sum	-9837818
Variance	215.5177474
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1	13474	2.4%
-2	13398	2.4%
0	13392	2.4%
-3	13237	2.4%
-4	13119	2.4%
-5	12949	2.3%
-6	12827	2.3%
-7	12606	2.3%
-8	12359	2.2%
-9	12224	2.2%
Other values (51)	339340	61.3%
(Missing)	84724	15.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-60	290	0.1%
-59	550	0.1%
-58	838	0.2%
-57	1081	0.2%
-56	1342	0.2%
-55	1631	0.3%
-54	1915	0.3%
-53	2162	0.4%
-52	2480	0.4%
-51	2821	0.5%

Value	Count	Frequency (%)
0	13392	2.4%
-1	13474	2.4%
-2	13398	2.4%
-3	13237	2.4%
-4	13119	2.4%
-5	12949	2.3%
-6	12827	2.3%
-7	12606	2.3%
-8	12359	2.2%
-9	12224	2.2%

STATUS
Real number (ℝ)

ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.6104842599

Minimum	-1
Maximum	5
Zeros	187137
Zeros (%)	33.8%
Negative	355798
Negative (%)	64.3%
Memory size	4.2 MiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	0
95-th percentile	0
Maximum	5
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.5989766712
Coefficient of variation (CV)	-0.9811500649
Kurtosis	18.56858721
Mean	-0.6104842599
Median Absolute Deviation (MAD)	0
Skewness	2.76919863
Sum	-337994
Variance	0.3587730527
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
-1	355798	64.3%
0	187137	33.8%
1	8166	1.5%
5	1282	0.2%
2	778	0.1%
3	280	0.1%
4	208	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	355798	64.3%
0	187137	33.8%
1	8166	1.5%
2	778	0.1%
3	280	0.1%
4	208	< 0.1%
5	1282	0.2%

Value	Count	Frequency (%)
5	1282	0.2%
4	208	< 0.1%
3	280	0.1%
2	778	0.1%
1	8166	1.5%
0	187137	33.8%
-1	355798	64.3%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	ID	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	AMT_INCOME_TOTAL	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	FLAG_MOBIL	FLAG_WORK_PHONE	OCCUPATION_TYPE	CNT_FAM_MEMBERS	AGE	YEARS_EMPLOYED	MONTHS_BALANCE	STATUS
0	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	0.0	-1
1	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-1.0	-1
2	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-2.0	-1
3	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-3.0	-1
4	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-4.0	-1
5	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-5.0	-1
6	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-6.0	-1
7	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-7.0	-1
8	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-8.0	-1
9	5008804	M	Y	Y	427500.0	Working	Higher education	Civil marriage	Rented apartment	1	1	NaN	2.0	32.868574	12.435574	-9.0	-1

Last rows

	ID	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	CNT_CHILDREN	AMT_INCOME_TOTAL	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	FLAG_MOBIL	FLAG_WORK_PHONE	OCCUPATION_TYPE	CNT_FAM_MEMBERS	AGE	YEARS_EMPLOYED	MONTHS_BALANCE	STATUS
553639	6836737	F	N	N	0	67500.0	Pensioner	Secondary / secondary special	Widow	House / apartment	1	0	NaN	1.0	59.609711	0.000000	NaN	-1
553640	6836990	M	N	N	0	360000.0	Commercial associate	Higher education	Separated	House / apartment	1	0	Managers	1.0	44.830489	1.659172	NaN	-1
553641	6837235	F	N	Y	0	135000.0	Working	Secondary / secondary special	Married	House / apartment	1	0	Laborers	2.0	37.205418	2.992532	NaN	-1
553642	6837264	F	N	N	2	90000.0	State servant	Higher education	Single / not married	House / apartment	1	0	Core staff	4.0	43.976262	3.490831	NaN	-1
553643	6837452	M	N	N	1	135000.0	Working	Secondary / secondary special	Separated	House / apartment	1	0	Security staff	2.0	35.516130	0.490085	NaN	-1
553644	6837707	M	N	Y	0	202500.0	Working	Higher education	Civil marriage	House / apartment	1	1	Laborers	2.0	36.989124	6.321827	NaN	-1
553645	6839651	F	N	Y	3	99000.0	Pensioner	Secondary / secondary special	Single / not married	House / apartment	1	0	NaN	1.0	51.560265	0.000000	NaN	-1
553646	6839917	F	N	Y	0	180000.0	Pensioner	Higher education	Married	House / apartment	1	0	NaN	2.0	30.023888	7.403301	NaN	-1
553647	6840104	M	N	Y	0	135000.0	Pensioner	Secondary / secondary special	Separated	House / apartment	1	0	NaN	1.0	62.197033	0.000000	NaN	-1
553648	6840222	F	N	N	0	103500.0	Working	Secondary / secondary special	Single / not married	House / apartment	1	0	Laborers	1.0	43.639500	8.232886	NaN	-1

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script